AI code looks perfect but feels wrong? After 30 years coding, I’ve learned the most valuable skill isn’t getting AI to write code – it’s knowing when to ignore it.
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Ever wonder why that AI-generated code feels *off* even when it looks perfectly fine?
After 30 years writing software and 8 years deep in AI solutions, I’ve learned something crucial: the most valuable skill isn’t getting AI to write code – it’s knowing when its confident answer is actually wrong.
AI coding assistants are incredible productivity boosters, but they have a dangerous quirk: they deliver every answer with the same unwavering confidence, whether it’s brilliant or completely fabricated. I’ve seen it hallucinate entire APIs that don’t exist, miss obvious edge cases, and generate security vulnerabilities while looking utterly professional.
Here’s what I’ve learned about making AI work for you instead of against you:
Trust your gut. When something feels disconnected from your project’s actual needs, dig deeper. AI follows patterns but can’t grasp context or business goals the way you can. That vague unease you feel? That’s decades of knowledge your brain can’t articulate but shouldn’t ignore.
Break everything into chunks. Small, focused prompts expose flaws earlier. One question at a time keeps you in control and catches problems before they compound.
Verify everything. Every suggestion gets manual review – especially for security and edge cases. The final 30% of any solution, where real-world complexity lives, is where AI falls apart most.
Stay sharp. The temptation to let AI handle everything is real, but skills fade fast. I deliberately practice manual problem-solving to keep my instincts honed.
The bottom line: AI is your assistant, not your authority. T
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